Interrupted time series analysis for impacts of day surgery on average days of stay

VernacularTitle:开展日间手术对平均住院日影响的间断时间序列分析
Author: Lei YUAN ¹ ; Liang LI ; Zhaoxin QIAN ; Xinyu CHEN ; Lingling PAN ; Qinghong WANG
Author Information

1. 中南大学湘雅医院医务部
Keywords: Day care; Day surgery; Average days of stay; Interrupted time series; Segmented regression analysis
From: Chinese Journal of Hospital Administration 2018;34(10):805-809
CountryChina
Language:Chinese
Abstract: Objective To evaluate the effects of day surgery on average days of stay, and to provide scientific basis for shorter average days of stay. Methods Data of average days of stay from November 2011 to December 2016 were extracted from 6 departments, Xiangya Hospital, Central South University. Segmented regression analysis of interrupted time series was used to analyze the trend of average days of stay of pre-and post-day surgery. Results Thanks to the application of day surgery, average days of stay decreased by 0. 071 days per month, and the monthly decline increased by 0. 049 days (P<0. 001) than before. Average days of stay in the department of stomatology, ear-nose-throat, general surgery and hepatobiliary & enteric surgery research center were the most obvious, and the monthly decline increased by 0. 110 days (P<0. 001), 0. 049 days (P=0. 008) , 0. 075 days (P<0. 001), and 0. 057 days (P=0. 003), respectively than before. Conclusions Day surgery could decrease average days of stay, enhancing the utilization of hospital resources.